How much we save universities
Universities save up to 80% on grading costs while improving consistency and speed across departments



80% Cost Reduction
Universities save on grading labor costs annually
Universities save up to 80% on grading costs while improving consistency and speed across departments



80% Cost Reduction
Universities save on grading labor costs annually
Streamlined assessment workflows that reduce administrative overhead and improve faculty productivity
80%
80% time saved
Track and analyze how universities benefit from automated grading and assessment solutions



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Automated Extraction
Instantly converts scanned exam papers into structured digital data. Our AI automatically identifies and maps student information, question numbers, and answer regions. No manual setup required.
30+ Languages
Arabic, Chinese, German & more
Compare & Validate
Complete control over results
Understands Every Answer
Intelligently processes diverse answer formats from handwritten essays to diagrams and mathematical equations. Adapts to any exam layout while maintaining accuracy across question types.
From handwritten essays to digital quizzes, GradeLab handles it all with the same precision and speed.

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Everything you need to automate grading with AI accuracy and teacher control.
Grade 200 handwritten exams in under 30 minutes. What takes 4 hours manually now takes 20 minutes with AI.
99%+ accuracy in reading handwritten answers across all subjects. Trained on millions of real student exams.
On-premise deployment keeps your exam data secure within your institution. Zero cloud dependency.
Grade essays, math problems, diagrams, MCQs, and mixed formats. Supports 30+ languages including Arabic and Chinese.
Review and adjust any AI grade with one click. You stay in control while AI handles the heavy lifting.
See class performance, question difficulty, and student progress the moment grading completes. Spot trends instantly.
They have structure. There is a hypothesis, a method, a data section, an analysis, and a conclusion. Each one needs specific feedback. Was the hypothesis testable? Was the method appropriate for the question being investigated? Was the data analysis correct, or did the student use the wrong statistical test? Was the conclusion supported by the data, or did the student overstate what the results showed?
Grading 40 lab reports takes hours because each one needs section-by-section evaluation. You read the hypothesis, you write a comment. You read the method, you write a comment. You check the data analysis, you write a comment. You read the conclusion, you write a comment. Then you do it again for the next report, and the next, and the next. By report 25 your comments are getting shorter. By report 40 you are writing "good" and "needs work" because you do not have time for more.
A lab report grader that understands this structure can do the first pass. GradeLab reads the report, evaluates each section against your rubric, and writes specific feedback. Was the hypothesis testable? Was the method appropriate? Was the data analysis correct? Was the conclusion supported by the data? You review, add your own comments, and approve.
Your students get better feedback because you have time to focus on the reports that need your expertise. The AI handles the first pass on the ones that are straightforward, and you spend your time on the ones where a student struggled with the analysis, or where the method was creative but flawed, or where the conclusion raised an interesting question. You can add custom instructions so the AI grades the way you would, and it applies your rules on every report, the same way, every time.
A lab report grader is AI software that reads lab reports and scores them section by section against your rubric. It evaluates the hypothesis, the method, the data analysis, and the conclusion separately, because each section has different criteria. It writes specific feedback for each section and returns a score with a breakdown so students understand exactly where they lost marks and why.
GradeLab lets you add your own custom instructions so the AI grades the way you would. Tell it to require error bars on all graphs. Tell it to check whether the student identified the control group. Tell it to flag conclusions that overstate the significance of the results. The AI applies your instructions on every report, consistently, whether it is report 1 or report 40.
You review every section score and feedback comment. You override, edit, or add your own observations. Nothing reaches a student until you approve it. The repetitive part, the part where you write the same comment about missing error bars for the tenth time, gets handled. The judgement part, the part where a student had a creative but flawed approach, stays with you.
GradeLab understands lab report structure. It evaluates the hypothesis, the method, the data analysis, and the conclusion separately, so each section gets the specific feedback it needs.
Watch how AI grading and online assessment work end-to-end, from upload to results.
GradeLab does not treat a lab report like a wall of text. It identifies each section, evaluates it against the right criteria, and gives specific feedback that helps students improve their scientific writing.
Was the hypothesis testable and clearly stated? The AI checks for specificity, testability, and alignment with the experiment described.
Was the method appropriate for the research question? Did the student identify controls, variables, and sample size? Feedback targets the specific gaps.
Did the student use the right statistical test? Were error bars included? Was the analysis correct and clearly presented? The AI flags specific issues.
Was the conclusion supported by the data? Did the student overstate significance or draw conclusions beyond the evidence? The AI catches common reasoning errors.
The AI is aware of APA, MLA, and Chicago citation conventions. Flag missing or malformed citations as a rubric criterion and the system factors them into the score.
Upload a full 10-page lab report or a 30-page research paper. The AI reads the entire document, evaluates each section across all pages, and returns a complete breakdown.
Write your rules in plain English. Require error bars, check for sample size, flag overstated conclusions. The AI follows your instructions on every report.
Upload all 40 reports at once. The system identifies each submission by filename or student ID, grades them in parallel, and compiles results into a single class report.
Review every section score and comment. Override, edit, add your own observations. Nothing reaches a student until you have approved it.
A side-by-side comparison of what changes when you switch from grading lab reports by hand to AI lab report grading with GradeLab.
| Metric | AI Lab Report Grading (GradeLab) | Manual Grading |
|---|---|---|
| Time per batch | Under 10 minutes for section-by-section suggestions | Hours of section-by-section reading and commenting |
| Section feedback | Specific feedback for hypothesis, method, data, conclusion | "good" and "needs work" by report 40 |
| Consistency | Same rubric on report 1 and report 40 | Comments get shorter as you get tired |
| Citation checking | APA, MLA, and Chicago auto-checked | Manual spot-check, if you remember |
| Scalability | Upload all 40 reports at once, graded in parallel | One report at a time, all weekend |
| Teacher control | Review, override, and add your own comments | You do everything by hand |
For research papers and term papers, use our paper grader. For full exam workflows, explore AI grading. For essays specifically, see our AI essay grader.
Governments, institutions, and AI ecosystems worldwide. Delivering secure, scalable, and accurate handwritten assessment solutions.

Official assessment workflows for certified exam bodies and large-scale handwritten examinations.
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Enterprise-grade AI grading deployed for national-level academic and workforce assessments.

Fine-tuned OCR and grading models built specifically for real-world exam handwriting.
Upload reports, get section-by-section feedback, review and release
Define criteria for each section: hypothesis, method, data analysis, and conclusion. Add custom instructions in plain English, like "require error bars on all graphs" or "deduct marks for missing sample size." The AI follows your rules on every report.
Upload digital files or scanned handwritten reports. GradeLab reads the entire document, identifies each section, and evaluates it against your rubric criteria.
Every report gets a per-section score and written feedback. Was the hypothesis testable? Was the method appropriate? Was the analysis correct? Was the conclusion supported by the data? You see the reasoning behind every mark.
Review every section score and feedback comment. Override, edit, or add your own observations. Approve when you are satisfied and release feedback to students, or sync to your LMS.
A lab report grader evaluates each section of a student lab report: hypothesis, method, data, analysis, and conclusion. It checks whether the hypothesis was testable, whether the method was appropriate, whether the data analysis was correct, and whether the conclusion was supported by the data. GradeLab does this first pass for you, applies your rubric, and writes specific feedback for each section.
Yes. You write your rules in plain English and GradeLab follows them. For example: "deduct marks if the hypothesis is not testable" or "award full marks for data analysis if the student used the correct formula even if the calculation has an arithmetic error." The AI applies your instructions on every report.
Yes. GradeLab understands the standard lab report structure: hypothesis, method, data, analysis, conclusion. It evaluates each section against your rubric and writes section-specific feedback. You review, add your own comments, and approve.
Yes. GradeLab handles research papers, term papers, and any structured academic writing. Upload the full document and the AI evaluates it against your rubric criteria, no matter the length.
Yes. Override any mark, rewrite any feedback, add your own comments, and finalize only after you are satisfied. Nothing reaches a student without your approval. The AI gives you a head start so you can focus on the reports that need your expertise.
Thomas Braun
Lecturer, Pure Mathematics, Germany
My students write formal mathematical proofs. On a convergence proof question, GradeLab correctly identified whether the quantifier structure was right, whether the chosen bound worked, and where the logical chain broke. It did not just check the final line. That is the part that matters.
Dr. Isabelle Fontaine
Associate Professor, Theoretical Physics, France
GradeLab evaluated a wavefunction normalisation problem across 140 papers and correctly flagged eleven cases where students had a correct final integral but had used the wrong boundary condition. That is precise, subject-aware marking.
Prof. James Fletcher
Mechanical Engineering, Thermodynamics, USA
GradeLab evaluated a question on entropy generation in a throttling process and correctly identified which students had omitted the system definition, which had applied the steady-flow energy equation incorrectly, and which had confused entropy change with entropy generation. That distinction matters in this subject and it caught it reliably.
Thomas Braun
Lecturer, Pure Mathematics, Germany
My students write formal mathematical proofs. On a convergence proof question, GradeLab correctly identified whether the quantifier structure was right, whether the chosen bound worked, and where the logical chain broke. It did not just check the final line. That is the part that matters.
Dr. Isabelle Fontaine
Associate Professor, Theoretical Physics, France
GradeLab evaluated a wavefunction normalisation problem across 140 papers and correctly flagged eleven cases where students had a correct final integral but had used the wrong boundary condition. That is precise, subject-aware marking.
Prof. James Fletcher
Mechanical Engineering, Thermodynamics, USA
GradeLab evaluated a question on entropy generation in a throttling process and correctly identified which students had omitted the system definition, which had applied the steady-flow energy equation incorrectly, and which had confused entropy change with entropy generation. That distinction matters in this subject and it caught it reliably.
Sophie Laurent
Science Teacher, Lycée Henri IV, Paris
Before GradeLab, I spent every Sunday grading papers instead of being with my family. Now I upload the batch on Friday evening and by Saturday morning, every student has already seen their feedback. That part still surprises me.
Maria Santos
Teacher, Escola Internacional de Lisboa
I teach four classes with 35 students each. I genuinely could not keep up with grading. GradeLab didn't just save me time - it gave me back the ability to actually know where each student was struggling.
Sarah Mitchell
Head of Academics, Wellington Grammar School
We trialled several edtech platforms before GradeLab. What stood out was that it wasn't just grading software - the student feedback loop was instant, and the quality reports for governors were exactly what we needed.
Sophie Laurent
Science Teacher, Lycée Henri IV, Paris
Before GradeLab, I spent every Sunday grading papers instead of being with my family. Now I upload the batch on Friday evening and by Saturday morning, every student has already seen their feedback. That part still surprises me.
Maria Santos
Teacher, Escola Internacional de Lisboa
I teach four classes with 35 students each. I genuinely could not keep up with grading. GradeLab didn't just save me time - it gave me back the ability to actually know where each student was struggling.
Sarah Mitchell
Head of Academics, Wellington Grammar School
We trialled several edtech platforms before GradeLab. What stood out was that it wasn't just grading software - the student feedback loop was instant, and the quality reports for governors were exactly what we needed.